A Novel Mutation in the MAP7D3 Gene in Two Siblings with Severe Intellectual Disability and Autistic Traits: Concurrent Assessment of BDNF Functional Polymorphism, X-Inactivation and Oxidative Stress to Explain Disease Severity.

Intellectual disabilities (ID) and autism spectrum disorders (ASD) are characterized by extreme genetic and phenotypic heterogeneity. However, understanding this heterogeneity is difficult due to the intricate interplay among multiple interconnected genes, epigenetic factors, oxidative stress, and environmental factors. Employing next-generation sequencing (NGS), we revealed the genetic cause of ID and autistic traits in two patients from a consanguineous family followed by segregation analysis. Furthermore, in silico prediction methods and 3D modeling were conducted to predict the effect of the variants. To establish genotype-phenotype correlation, X-chromosome inactivation using Methylation-specific PCR and oxidative stress markers were also investigated. By analyzing the NGS data of the two patients, we identified a novel frameshift mutation c.2174_2177del (p.Thr725MetfsTer2) in the MAP7D3 gene inherited from their mother along with the functional BDNF Val66Met polymorphism inherited from their father. The 3D modeling demonstrated that the p.Thr725MetfsTer2 variant led to the loss of the C-terminal tail of the MAP7D3 protein. This change could destabilize its structure and impact kinesin-1's binding to microtubules via an allosteric effect. Moreover, the analysis of oxidative stress biomarkers revealed an elevated oxidative stress in the two patients compared to the controls. To the best of our knowledge, this is the first report describing severe ID and autistic traits in familial cases with novel frameshift mutation c.2174_2177del in the MAP7D3 gene co-occurring with the functional polymorphism Val66M in the BDNF gene. Besides, our study underlines the importance of investigating combined genetic variations, X-chromosome inactivation (XCI) patterns, and oxidative stress markers for a better understanding of ID and autism etiology.

Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs.

Causal loss-of-function (LOF) variants for Mendelian and severe complex diseases are enriched in 'mutation intolerant' genes. We show how such observations can be interpreted in light of a model of mutation-selection balance and use the model to relate the pathogenic consequences of LOF mutations at present to their evolutionary fitness effects. To this end, we first infer posterior distributions for the fitness costs of LOF mutations in 17,318 autosomal and 679 X-linked genes from exome sequences in 56,855 individuals. Estimated fitness costs for the loss of a gene copy are typically above 1%; they tend to be largest for X-linked genes, whether or not they have a Y homolog, followed by autosomal genes and genes in the pseudoautosomal region. We compare inferred fitness effects for all possible de novo LOF mutations to those of de novo mutations identified in individuals diagnosed with one of six severe, complex diseases or developmental disorders. Probands carry an excess of mutations with estimated fitness effects above 10%; as we show by simulation, when sampled in the population, such highly deleterious mutations are typically only a couple of generations old. Moreover, the proportion of highly deleterious mutations carried by probands reflects the typical age of onset of the disease. The study design also has a discernible influence: a greater proportion of highly deleterious mutations is detected in pedigree than case-control studies, and for autism, in simplex than multiplex families and in female versus male probands. Thus, anchoring observations in human genetics to a population genetic model allows us to learn about the fitness effects of mutations identified by different mapping strategies and for different traits.

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment.

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels.

PURPOSE: Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not. METHODS: Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship. RESULTS: As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants. CONCLUSION: Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.

Assessment of Peripheral Blood Lymphocytes in Parents of Autistic Children by Cytokinesis Block Micronucleus Assay.

Autism spectrum disorders are neurodevelopmental complex diseases with causative de-novo and inherited genetic factors. They include a range of cognitive and behavioral conditions such as pervasive developmental disorder, Asperger's syndrome, and autism. Cytokinesis-block micronucleus assay, as a cytogenetic study has been considered as one of the indicators of chromosomal damage in peripheral blood. This study aimed to investigate the frequency of micronucleus (MN) in peripheral blood lymphocytes of parents with autistic children. The study was case-control and the cases were parents of autistic children referring to the psychiatric department of the Ali-Asghar Hospital of Tehran. The total number of samples was 60 cases and 30 controls. The results showed that autistic children's parents had a significant increase in MN frequency in binucleated lymphocytes. Further researches are suggested to analyze the environmental and genetic reasons for MN increase in autistic children parents.

An overview of modeling and behavioral assessment of autism in the rodent.

Autism Spectrum Disorders (ASDs) are common neurodevelopmental disorders with a growing incidence that generally present in the first 3 years of life. Behavioral symptoms, including impaired social interaction and increased repetitive or stereotypic movements, are hallmark characteristics of autism. Animal models are research tools used to study the biology of the disease and to develop new therapeutic approaches. The complexity of the etiology of autism makes it challenging to develop a comprehensive animal model that accurately mimics different clinical aspects of autism. Here, we reviewed the literature on modeling and behavioral assessment of autism in the rodent, and focused on ASD behavioral phenotypes that can be modeled in rodents. These animal models can be effective in gaining a better understanding of the pathophysiology of the disease.

Assessment of autism-relevant behaviors in C57BKS/J leptin receptor deficient mice.

Gestational diabetes mellitus (GDM) was associated with greater autism risk in epidemiological studies. Disrupted leptin signaling may contribute to their coincidence, as it is found in both disorders. Given this we examined leptin receptor (Lepr) deficient (BKS.Cg-Dock7m +/+ Leprdb/J diabetic (db)) heterozygous (db/+) mice for autism-relevant behaviors. BKS db/+ females are lean with normal blood glucose, but they develop GDM while pregnant. We hypothesized BKS db/+ offspring might exhibit physiological and behavior traits consistent with autism. Adolescent body weight, fasting blood glucose, serum corticosterone, social preferences, self-grooming, marble burying, social dominance and cognitive flexibility of BKS db/+ mice was compared to C57BLKS/J (BKS) and C57BL/6J (BL6) mice. Male db/+ weighed more and had higher blood glucose and corticosterone relative to BL6, but not BKS mice. Also, male db/+ lacked social interaction preference, explored arenas less, and buried more marbles than BL6, but not BKS males. Male and female db/+ were more dominant and made more mistakes in water T-mazes locating a sunken platform after its position was reversed than BL6, but not BKS mice. Overall BKS db/+, particularly males, exhibited some autism-like social deficits and restrictive-repetitive behaviors relative to BL6, but BKS strain contributions to BKS db/+ behaviors were evident. Since BKS db/+ and BKS behavioral and physiological phenotypes are already so similar, it will be difficult to use these models in studies designed to detect contributions of fetal GDM exposures to offspring behaviors.

Assessment of Apoptosis Pathway in Peripheral Blood of Autistic Patients.

Autism spectrum disorder (ASD) includes a number of severe neurodevelopmental disorders known by defects in social interaction, impaired verbal and non-verbal interactions, and stereotypic activities and limited interests. Dysregulation of apoptotic pathways have been demonstrated in brain tissues of affected individuals. In the present study, we evaluated expression levels of apoptosis-related genes and miRNAs in peripheral blood of ASD patients compared with healthy subjects. Transcript levels of BCL2, CASP8, and hsa-29c-3p were significantly lower in total ASD patients compared with total normal children (P values = 0.003, 0.002, and 0.01 respectively). When sex of study participants was considered in the analysis, the difference in transcript levels of these genes was significant only in male subjects. Peripheral expression of BCL2 and hsa-29c-3p had 100% sensitivity 92% specificity in ASD diagnosis. The diagnostic power of combination of transcript levels of these genes was estimated to be 78% based on the calculated AUC value. The present study provides evidences for dysregulation of apoptotic pathways in peripheral blood of ASD patients and suggests certain apoptosis-related genes as biomarkers in this regard.

Genomic trade-offs: are autism and schizophrenia the steep price of the human brain?

Evolution often deals in genomic trade-offs: changes in the genome that are beneficial overall persist even though they also produce disease in a subset of individuals. Here, we explore the possibility that such trade-offs have occurred as part of the evolution of the human brain. Specifically, we provide support for the possibility that the same key genes that have been major contributors to the rapid evolutionary expansion of the human brain and its exceptional cognitive capacity also, in different combinations, are significant contributors to autism and schizophrenia. Furthermore, the model proposes that one of the primary genes behind this trade-off may not technically be "a gene" or "genes" but rather are the highly duplicated sequences that encode the Olduvai protein domain family (formerly called DUF1220). This is not an entirely new idea. Others have proposed that the same genes involved in schizophrenia were also critical to the rapid expansion of the human brain, a view that has been expressed as "the same 'genes' that drive us mad have made us human". What is new is that a "gene", or more precisely a protein domain family, has been found that may satisfy these requirements.

Assessment of Cognitive Outcome Measures in Teenagers with 15q13.3 Microdeletion Syndrome.

15q13.3 microdeletion syndrome causes a spectrum of cognitive disorders, including intellectual disability and autism. We aimed to determine if any or all of three cognitive testing systems (the KiTAP, CogState, and Stanford-Binet) are suitable for assessment of cognitive function in affected individuals. These three tests were administered to ten individuals with 15q13.3 microdeletion syndrome (14-18 years of age), and the results were analyzed to determine feasibility of use, potential for improvement, and internal consistency. It was determined that the KiTAP, CogState, and Stanford-Binet are valid tests of cognitive function in 15q13.3 microdeletion patients. Therefore, these tests may be considered for use as objective outcome measures in future clinical trials, assessing change in cognitive function over a period of pharmacological treatment.

Adjudicating non-knowledge in the Omnibus Autism Proceedings.

After 5600 families of children diagnosed with autism filed claims with the National Vaccine Injury Compensation Program in the United States, the court selected 'test' cases consolidated into the Omnibus Autism Proceedings, held from 2007 to 2008, to examine claims that vaccines caused the development of autism. The court found all of the causation theories presented to be untenable and did not award damages to any parents. We analyze the Omnibus Autism Proceedings as a struggle within the scientific field between the scientific orthodoxy of the respondents and the heterodox position taken by the plaintiffs, suggesting that the ruling in these cases helped to shore up hegemony on autism causation. Drawing on the literature on non-knowledge, we suggest that only the respondents had enough scientific capital to strategically direct non-knowledge toward genetic research, thereby foreclosing the possibility of environmental causation of autism. The plaintiffs, who promote a non-standard ontology of autism, suggest that the science on autism remains undone and should not be circumscribed. In analyzing the Omnibus Autism Proceedings with field theory, we highlight the way in which scientific consensus-building and the setting of research agendas are the result of struggle, and we show that the strategic deployment of non-knowledge becomes a major stake in battles for scientific legitimacy and the settling of scientific controversies.

Diagnosis of autism, abortion and the ethics of childcare in Yoruba culture.

This paper examines the ethics of childcare in Yoruba culture in the contexts of autism and abortion. The traditional Yoruba moral principles of ibikojuibi (equality of humans at birth) and ajowapo (solidarity) have been theoretically developed to establish the personhood of autistic children and provide a justification for not aborting foetuses with autism. Despite these justifications, this paper argues that there is a need for contextual rethinking, which would allow for: (i) prenatal genetic testing, as well as abortion of foetuses with a high risk of the autism mutation, and (ii) early clinical diagnosis and treatment of autistic children in contemporary Yoruba society.

Autism as a disorder of prediction.

A rich collection of empirical findings accumulated over the past three decades attests to the diversity of traits that constitute the autism phenotypes. It is unclear whether subsets of these traits share any underlying causality. This lack of a cohesive conceptualization of the disorder has complicated the search for broadly effective therapies, diagnostic markers, and neural/genetic correlates. In this paper, we describe how theoretical considerations and a review of empirical data lead to the hypothesis that some salient aspects of the autism phenotype may be manifestations of an underlying impairment in predictive abilities. With compromised prediction skills, an individual with autism inhabits a seemingly "magical" world wherein events occur unexpectedly and without cause. Immersion in such a capricious environment can prove overwhelming and compromise one's ability to effectively interact with it. If validated, this hypothesis has the potential of providing unifying insights into multiple aspects of autism, with attendant benefits for improving diagnosis and therapy.

Assessing the impact of copy number variants on miRNA genes in autism by Monte Carlo simulation.

Autism Spectrum Disorders (ASDs) are childhood neurodevelopmental disorders with complex genetic origins. Previous studies have investigated the role of de novo Copy Number Variants (CNVs) and microRNAs as important but distinct etiological factors in ASD. We developed a novel computational procedure to assess the potential pathogenic role of microRNA genes overlapping de novo CNVs in ASD patients. Here we show that for chromosomes # 1, 2 and 22 the actual number of miRNA loci affected by de novo CNVs in patients was found significantly higher than that estimated by Monte Carlo simulation of random CNV events. Out of 24 miRNA genes over-represented in CNVs from these three chromosomes only hsa-mir-4436b-1 and hsa-mir-4436b-2 have not been detected in CNVs from non-autistic subjects as reported in the Database of Genomic Variants. Altogether the results reported in this study represent a first step towards a full understanding of how a dysregulated expression of the 24 miRNAs genes affect neurodevelopment in autism. We also propose that the procedure used in this study can be effectively applied to CNVs/miRNA genes association data in other genomic disorders beyond autism.

Identification of rare variants from exome sequence in a large pedigree with autism.

We carried out analyses with the goal of identifying rare variants in exome sequence data that contribute to disease risk for a complex trait. We analyzed a large, 47-member, multigenerational pedigree with 11 cases of autism spectrum disorder, using genotypes from 3 technologies representing increasing resolution: a multiallelic linkage marker panel, a dense diallelic marker panel, and variants from exome sequencing. Genome-scan marker genotypes were available on most subjects, and exome sequence data was available on 5 subjects. We used genome-scan linkage analysis to identify and prioritize the chromosome 22 region of interest, and to select subjects for exome sequencing. Inheritance vectors (IVs) generated by Markov chain Monte Carlo analysis of multilocus marker data were the foundation of most analyses. Genotype imputation used IVs to determine which sequence variants reside on the haplotype that co-segregates with the autism diagnosis. Together with a rare-allele frequency filter, we identified only one rare variant on the risk haplotype, illustrating the potential of this approach to prioritize variants. The associated gene, MYH9, is biologically unlikely, and we speculate that for this complex trait, the key variants may lie outside the exome.

Genetic studies of complex human diseases: characterizing SNP-disease associations using Bayesian networks.

BACKGROUND: Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis, and treatment of complex human diseases. Applying machine learning or statistical methods to epistatic interaction detection will encounter some common problems, e.g., very limited number of samples, an extremely high search space, a large number of false positives, and ways to measure the association between disease markers and the phenotype. RESULTS: To address the problems of computational methods in epistatic interaction detection, we propose a score-based Bayesian network structure learning method, EpiBN, to detect epistatic interactions. We apply the proposed method to both simulated datasets and three real disease datasets. Experimental results on simulation data show that our method outperforms some other commonly-used methods in terms of power and sample-efficiency, and is especially suitable for detecting epistatic interactions with weak or no marginal effects. Furthermore, our method is scalable to real disease data. CONCLUSIONS: We propose a Bayesian network-based method, EpiBN, to detect epistatic interactions. In EpiBN, we develop a new scoring function, which can reflect higher-order epistatic interactions by estimating the model complexity from data, and apply a fast Branch-and-Bound algorithm to learn the structure of a two-layer Bayesian network containing only one target node. To make our method scalable to real data, we propose the use of a Markov chain Monte Carlo (MCMC) method to perform the screening process. Applications of the proposed method to some real GWAS (genome-wide association studies) datasets may provide helpful insights into understanding the genetic basis of Age-related Macular Degeneration, late-onset Alzheimer's disease, and autism.